Upstream Solar Wind Conditions at Mercury During the First two MESSENGER Flybys

The knowledge of upstream solar wind conditions at Mercury is essential not only for modeling the Hermian magnetosphere-exosphere-surface system but also for interpreting the pioneering in situ observations made by MESSENGER during the January and October 2008 flybys. For this reason, and due to the fact that the MESSENGER plasma instruments cannot see the solar wind, we intend to provide upstream solar wind conditions at Mercury to the entire MESSENGER community. We do this using a combination of two independent solar wind models. The first is a steady-state 3-D magnetohydrodynamic (MHD) model of the solar corona and inner heliosphere, which simulates the solar wind propagation from the source surface outward to Mercury, using synoptic charts of the photospheric magnetic field as input. The second model is a time-dependent 1-D MHD model of solar wind propagation that employs actual solar wind data at 1 AU as boundary conditions and propagates the solar wind backward in time to Mercury. Although the latter approach is a rather unorthodox way of simulating the solar wind, the method is well tested. We first test the reversibility of the method by propagating the simulation results at Mercury back to Earth (forward in time). The backward and forward propagated solar wind at Earth was found to be practically identical with the original input indicating that the backward propagation does not result in problems with conservation. As a second test, we compare results from the two models. The relatively good agreement between the predictions of the two models verifies that the reverse propagation method can be successfully applied in estimating solar wind conditions at Mercury. The agreement between the two models is best for the solar wind plasma data (speed, density and temperature) and less convincing for the magnetic field data, which can be attributed to the necessary a priori constraints of the magnetic field inherent in both models. Limitations and advantages of both modeling approaches are discussed.